Abstract
Detection of new or rapidly evolving melanocytic lesions is crucial for early diagnosis and treatment of melanoma. We propose a fully automated pre-screening system for detecting new lesions or changes in existing ones, on the order of 2 − 3mm, over almost the entire body surface. Our solution is based on a multi-camera 3D stereo system. The system captures 3D textured scans of a subject at different times and then brings these scans into correspondence by aligning them with a learned, parametric, non-rigid 3D body model. This means that captured skin textures are in accurate alignment across scans, facilitating the detection of new or changing lesions. The integration of lesion segmentation with a deformable 3D body model is a key contribution that makes our approach robust to changes in illumination and subject pose.
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Bogo, F., Romero, J., Peserico, E., Black, M.J. (2014). Automated Detection of New or Evolving Melanocytic Lesions Using a 3D Body Model. In: Golland, P., Hata, N., Barillot, C., Hornegger, J., Howe, R. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014. MICCAI 2014. Lecture Notes in Computer Science, vol 8673. Springer, Cham. https://doi.org/10.1007/978-3-319-10404-1_74
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DOI: https://doi.org/10.1007/978-3-319-10404-1_74
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